A Comparison of two different jet algorithms for the top mass reconstruction at the LHC

TL;DR

The paper evaluates two jet algorithms—the mid-point iterating cone and the k_T clustering algorithm—for reconstructing the top quark mass in LHC ttbar events. It leverages the additional information in cluster-merging scales via a Fisher discriminant to decide jet multiplicity and compares performance using MC@NLO/HERWIG/JIMMY and ALPGEN MLM-generated samples. Key findings show that cone jets have better mass resolution while k_T jets exhibit different dominant systematics (ISR/UE) compared to FSR-dominated cone systematics; importantly, their systematic errors are largely complementary. The study suggests that combining information from both algorithms could yield a more precise top mass measurement at the LHC and better constrain non-perturbative effects such as hadronisation and the underlying event.

Abstract

We compare the abilities of the cluster-type jet algorithm, KtJet, and a mid-point iterating cone algorithm to reconstruct the top mass at the LHC. We discuss the information contained in the merging scales of cluster-type algorithms, and how this can be used in experimental analyses, as well as the different sources of systematic errors for the two algorithms. We find that the sources of systematic error are different for the two algorithms, which may help to better constrain the systematic error on the top mass at the LHC.

Figures (2)

• Figure 1: Schematic representation of the LO Feynman diagrams for $t\bar{t}$ production.
• Figure 2: A higher order correction to top decay.